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Published in final edited form as: AIDS Care. 2020 Mar 12;32(SUP2):99–106. doi: 10.1080/09540121.2020.1739206

AIDSImpact Special Issue: Mobilizing individual social capital resources for HIV care support: results of a pilot intervention in St. Petersburg, Russia

Yuri A Amirkhanian 1,2, Jeffrey A Kelly 1, Anna V Kuznetsova 2, Wayne J DiFranceisco 1, Sergey S Tarima 1, Timothy L McAuliffe 1, Dmitry G Pirogov 2,3, Alexey A Yakovlev 4,5, Vladimir B Musatov 4,5, Nikolay A Chaika 6
PMCID: PMC7175397  NIHMSID: NIHMS1578894  PMID: 32162527

Abstract

Less than half of people living with HIV (PLH) in Russia are on antiretroviral therapy (ART), and only 27% are virally suppressed. Interventions to better engage PLH in medical care could reduce onward transmission and also improve health. A feasibility pilot test of an intervention to increase social capital to support HIV care engagement was carried out in St. Petersburg. Out-of-care or care-nonadherent PLH (n=24) attended a five-session group intervention to (1) help participants enter care, initiate ART, and adhere to ART and (2) identify and access social capital resources—such as family members, friends, and care providers—to mobilize their supports for HIV care. Participants were assessed at baseline, at followup immediately after intervention (FU-1), and again at 6-month followup (FU-2) with HIV viral load testing and measures of HIV care engagement, ART adherence, and social capital. At FU-1, participants reported talking more frequently and with a greater number of friends about HIV care experiences, verifying the intervention’s mechanism of action. Participants increased in scores on scales measuring medication-taking adherence (p=0.002 at FU-1 and p=0.011 at FU-2), HIV medication-taking self-efficacy (p=0.042 at FU-1), and HIV medication-taking outcome expectancies (at FU-2, p=0.016 among persons on ART and p=0.026 among those not on ART). HIV Medication Readiness scale scores increased at FU-1 (p=0.032) among persons not on ART, although some changes became attenuated over time. Participants tended to keep their care appointments more frequently (79% at baseline to 90% at FU-1; p=0.077); to have undetectable viral load (54% at baseline to 74% at FU-2; p=0.063); and to have fewer days in the past month with delayed or incomplete medication doses (from 7.8 at baseline to 4.2 at FU-1; p=0.084). This social capital intervention is novel and promising for improving HIV care-related outcomes, and warrants a full-scale evaluation.

Keywords: HIV care engagement, intervention, Russia, social capital, social networks

Introduction

Russia is among few countries in the world with an expanding HIV epidemic. Approximately 1,000 HIV infections had been diagnosed in Russia by 1996 (UNAIDS, 1998). However, an explosive increase followed, with over 1.3 million HIV infections diagnosed by 2019. Russia’s HIV incidence rate has consistently remained at 10% over the past decade (UNAIDS, 2018), in sharp contrast to most other European countries that have seen declines (Cousins, 2017). Russia’s HIV epidemic was initially fueled by drug use, but sexual transmission is now predominant (Russian Federal AIDS Center, 2015).

Only about one-third of persons living with HIV infection (PLH) in Russia—or approximately half of those diagnosed as HIV-positive—receive antiretroviral therapy (ART) (Russian Federal AIDS Center, 2017; UNAIDS, 2018). Over 20% of persons who initiate ART in Russia later discontinue the therapy. With only 27% of PLH in Russia believed to be virally suppressed (UNAIDS, 2018), Russia’s still-expanding HIV epidemic is fueled by the high proportion of PLH with unsuppressed viral load and correspondingly high potential for transmitting the disease.

Insufficient HIV care engagement and poor ART coverage in Russia are linked to structural barriers including a highly-centralized, underfunded, and fragmented HIV care system. On an individual level, poor social support is a key barrier to care engagement (Kuznetsova, et al., 2018). There are strong and consistent relationships between social support and care engagement and adherence (Khamarko & Myers, 2013; Malta et al., 2008). Alone, or in association with other factors, social support predicts ART adherence (Amberbir et al., 2008; Catz et al., 2000; Harris et al., 2011; Peltzer et al., 2010; Remien et al., 2003; Tiyou et al., 2010), virologic outcomes and CD4+ cell progression (Alemu et al., 2012; Chang et al., 2010; Knowlton et al., 2007; Simoni et al., 2006), and health-related quality of life (Khumsaen et al., 2012; Johnson et al., 2012; Rotheram-Borus et al., 2010; Wohl et al., 2011). In Russia, lack of social support, stigma, mental health problems, and substance use are associated with adverse HIV health outcomes (Edelman et al., 2017; Desrosiers et al., 2017; Kiriazova et al., 2017; Pecoraro et al., 2015; Goodness et al., 2014). Poor social support exacerbates the impact of life stressors by reducing capacity for adaptation (Lazarus & Folkman, 1984; Wills & Fegan, 2001).

Social capital interventions have been carried out to address a number of public health issues (Villalonga-Olives et al., 2018), but none focused on HIV/AIDS. As first articulated by Bourdieu (1987), Coleman (1988; 1990), Putnam (1993), and others, social capital refers to resources that derive from one’s social relationships (James et al., 2001). Social capital is usually conceptualized as a combination of social engagement, support, and person-to-person contact. Communities with high social capital resources and opportunities have more favorable public health indicators than those with few resources, even when comparable in socioeconomic distress (Cattrell, 2001; Fuchs et al., 2001; James et al., 2001; Kawachi et al., 2008). In the context of PLH, social capital can include support not only from HIV-positive peers but also from a potentially much broader resources including friends, acquaintances, family members, community members or groups, formal or informal caregivers, or advocacy organizations. Community indicators of social capital—that is, greater opportunities for social connectedness—are associated with earlier HIV diagnosis, improved linkage and retention in HIV medical care, and higher ART adherence (Campbell et al., 2002; 2012; 2013; Cattell, 2001; Frumence et al., 2010; Gibbs et al., 2014; Holtgrave et al., 2003; Poundstone et al., 2004; Ransome et al., 2016, 2017a, 2017b; Ware et al., 2009).

Lin’s Network Theory of Social Capital (Lin, 1999a; 1999b; 2001) guided the intervention pilot tested in this research. The framework is conceptualized in terms of (a) resources embedded in a social structure; (b) accessibility of these social resources by individuals; and (c) use or mobilization of these resources for purposive action. In the context of the present study, purposive action refers to care engagement and adherence. The theory posits that social capital resources can serve to enhance the outcomes of individuals’ actions by facilitating the flow of information about opportunities and choices, by improving decision-making, by providing the individual with social credentials in the eyes of others, and by reinforcing a positive sense of self-esteem, recognition, and worthiness (Lin, 1999a). Positive outcomes produced by social capital can be viewed as a consequence of mobilizing or using resources that are embedded in social networks.

This study reports the results of an innovative pilot intervention to help PLH to develop or mobilize individual social capital resources to support HIV care. The study evaluated changes over time in participants’ HIV care engagement, ART adherence, and HIV viral load, comparing their baseline characteristics with those collected at an immediate post-intervention followup (FU-1) and at 6-month followup (FU-2).

Materials and Methods

Settings and Participant Enrollment

This research was carried out in 2018 in St. Petersburg, Russia. It was approved by the Medical College of Wisconsin IRB and by the Local Ethics Committee of Botkin Hospital for Infectious Diseases. Twenty-four PLH were recruited through announcements placed on websites and other virtual spaces such as PLH-oriented online discussion boards, forums, and online social network groups. Enrollment criteria included: (1) HIV+ serostatus confirmed by blood testing, (2) reporting no HIV medical care visit in the past 6 months or—if prescribed ART—taking medication doses on <90% of days in the past month, and (3) being age 18 or older.

Assessment Measures

Consented participants attended assessment visits at the Botkin Hospital study office at baseline, immediate followup, and 6-month followup points, and received an incentive payment of approximately $15 for each visit. The assessment consisted of an individually-administered interview and biological specimen collection.

Demographic Characteristics and HIV Treatment History

These measures included age, gender, education, relationship status, length of serostatus knowledge, exposure risk history, and HIV treatment and ART history.

HIV Care Attendance, Appointment Keeping, and ART Adherence

Participants were asked how many HIV medical care appointments were scheduled and how many were missed in the past 6 months. Three measures of adherence were employed. Participants first completed the Visual Analog Scale (VAS), previously shown valid for measuring ART adherence (Kalichman et al., 2009), to indicate the percentage of medication doses taken as prescribed in the past week. In addition, participants specified the number of days in the past month when they missed taking medication or delayed or took incomplete doses. Finally, participants completed the Special Project of National Significance (SPNS) ART adherence scale, a measure with well-established psychometric characteristics (Julian et al., 2010).

HIV Medication Readiness and HIV Medication-Taking Self-Efficacy Scales

Participants not presently on ART regimens were administered 9 items of the HIV Medication Readiness Scale (Balfour et al., 2007). All participants completed the HIV Medication-Taking Self-Efficacy Scale (Erlen et al, 2010) that consisted of two subscales, Self-Efficacy Beliefs (SEB) and Outcome Expectancy (OE). All Cronbach alphas exceeded 0.92.

Social Capital Assessment

The Social Network Index (SNI) assessed individuals’ social capital resources (Cohen et al., 1997) reflecting their participation in relationships with a spouse or a partner, immediate and more distant family members, friends, work- and schoolmates, as well as members of different groups with which participants are affiliated. Three quantitative variables are derived from this assessment: (1) diversity of the resource network; (2) number of people in the resource network; and (3) number of different network domains in which a respondent is active.

HIV and Viral Load Testing

Study nurses performed a blood draw analyzed to verify participants’ HIV-positive serostatus and to determine viral load at each assessment, expressed as number of copies per mL and defined as undetectable if <40 copies/mL, a stringent cutoff that reflects a high level of viral suppression. Laboratory procedures were performed by an infectious disease hospital experienced in viral load testing.

Intervention Exposure

Intervention exposure was measured by asking participants to report the number of times and the number of HIV-positive persons with whom in the past month they discussed experiences related to being HIV-positive, experiences with ART, and HIV medical care experiences.

The Intervention

The intervention was designed to achieve two parallel purposes: (1) to move participants towards personal HIV goals related to care engagement, attendance, and adherence, and (2) to identify, access, and mobilize social capital resources to provide both general psychosocial support and to support participants’ efforts to move towards their HIV care goals. The intervention consisted of five weekly sessions each lasting 2.5 hours, led by two professional facilitators, and attended by 12 participants per group.

Sessions addressed gaining informational, emotional, appraisal, and tangible support for engaging in HIV medical care, attending appointments, remaining in care, adhering to ART regimens, and addressing life problems that could interfere with care engagement. Participants were guided in developing and mobilizing personally-relevant social capital resources. For individuals who already had potentially supportive persons or groups in their social environment, the intervention sought to mobilize or increase the frequency and quality of interaction with these support resources, including sensitive issues such as whether, when, and with whom to disclose HIV serostatus. For individuals socially isolated from others, the intervention encouraged the development of new ties through participation in self-support groups and activities to expand overall social capital resources.

Sessions employed interactive group discussion, role plays, skills building exercises, group problem-solving, and goal-setting for activities between sessions. Time was spent in each session assisting participants in setting weekly goals to seek out opportunities to interact with one or more of the identified social resources, to engage in shared activities, or to identify and access at least one new social resource. Participants also discussed with one another challenges and care barriers they face, and life concerns that they have.

Data Analysis

Data analysis consisted of univariate tests of within-subjects change among participants from baseline to FU-1 and baseline to FU-2 assessments. For categorical indicators, the statistical significance of changes was established using McNemar’s test for dichotomous repeated measures, and using paired-sample t-tests for mean differences between assessments for continuous variables. Because our intent was to establish preliminary intervention efficacy with a sample of modest size, p values of ≤0.10 are included in the Results. Only variables that showed significance or trend-level changes over time are presented in Table 1.

Table 1.

Baseline to Immediate Followup and Baseline to 6-Month Followup Comparisons of Social Capital Intervention Outcomes Among a Pilot Sample of 24 HIV-Positive Participants in St. Petersburg, Russia

Variable Baseline (n=24) Post-Intervention Followup (n=24) Baseline to Post-Intervention Followup Pa 6-Month Followup (n=23) Baseline to 6-Month Followup Pa
HIV Viral Suppression and Care Appointment Attendance:
 Undetectable viral load (< 40 copies/mL) 54.2% (13) 66.7% (16) 0.375 73.9% (17) 0.063
 Percent of HIV physician appointment kept in the past 6 months—Mean (SE) 78.5 (8.42) 89.6 (6.00) 0.077 91.7 (5.11) 0.212
Adherence to ART Medications:
 Number of days with delayed ART taking or taking an incomplete dose in the past month—Mean (SE) 7.8 (2.19) 4.2 (1.56) 0.084 4.8 (1.91) 0.240
 SPNS ART Adherence Scale—Mean (SE) 10.5 (0.86) 12.9 (0.74) 0.002 12.4 (0.76) 0.011
 VAS Percent medications taken in the past week—Mean (SE) 82.9 (7.47) 98.4 (1.58) 0.059 97.3 (1.51) 0.061
HIV Medication Readiness and HIV Medication-Taking Self-Efficacy:
 ART medication-taking self-efficacy scale among all participants —Mean (SE) 9.1 (0.31) 9.5 (0.18) 0.042 9.3 (0.21) 0.361
 ART medication-taking outcome expectancy scale among all participants—Mean (SE) 8.6 (0.43) 9.1 (0.35) 0.053 9.3 (0.36) 0.016
 ART medication-taking outcome expectancy scale among participants not on ART—Mean (SE) 7.1 (1.03) 8.1 (1.08) 0.129 8.3 (1.09) 0.026
 ART medication-taking readiness scale among participants not on ART —Mean (SE) 23.8 (4.79) 27.0 (4.38) 0.032 24.0 (5.86) 0.371
Social Capital Assessment Measures:
 Network diversity—Mean (SE) 5.4 (0.41) 6.2 (0.49) 0.068 6.2 (0.47) 0.165
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For categorical data, statistical significance was evaluated using McNemar’s test for dichotomos related variables. For continuous variables, significance was evaluated by paired-sample T-tests.

Results

Participants

Participants’ mean age was 33.7 years. 17 participants were males and 7 were females, and 50% (n=12) were married or in relationships. Most participants (58%, n=14) completed high school and 29% (n=7) had a university degree. Approximately 50% of participants had a history of injecting drugs. One-quarter of participants (n=6) had an exclusively homosexual orientation and three-quarters (n=18) were exclusively heterosexual.

Intervention Attendance and Verification of Intervention Exposure

Eighty-seven percent (n=20) of participants completed all intervention sessions. The intervention sought to increase both the number of persons with whom HIV care issues could be discussed, as well as the frequency of conversations with these persons regarding HIV care goals. These interactions constituted the active ingredient of the intervention. Baseline to FU-1 comparisons showed significant increases in the mean number of persons with whom participants discussed HIV care (3.5 vs 5.6, p=0.043) and experiences of living with HIV (4.1 vs 9.8, p=0.017). Significant increases were also found for frequency of conversations with friends about HIV care (3.2 vs 9.1, p=0.005), ART (4.9 vs 9.9, p=0.041), and experiences of living with HIV (10.3 vs 16.5, p=0.023), verifying substantial increases in interactions of the kinds that were expected to be produced by the intervention.

Intervention Outcomes

Evidence of benefit was found on a wide range of HIV care outcome indicators. Changes between baseline and the FU-1 and FU-2 points are shown in Table 1.

HIV viral suppression and care appointment attendance

At baseline, 54% of participants had undetectable viral load, and this proportion increased to 74% at 6-month followup, a 37% relative increase from the baseline proportion that represented a statistical trend. The mean percentage of HIV care appointments kept in the past 6 months increased from 79% at baseline to 90% at FU-1, also a trend.

Adherence to ART medications

Suboptimal HIV medication adherence was defined as taking <90% of prescribed doses. As Table 1 shows, there were significant improvements between baseline and both followup points for ART adherence as measured by SPNS medication-taking adherence scale. In addition, past-week medication adherence measured by the VAS showed a strong trend for change, from 83% adherence at baseline to 98% and 97% at FU-1 and FU-2, respectively. Finally, there was a trend for reduction in the mean number of days with delayed or incomplete medication doses, from 7.8 at baseline to 4.2 at FU-1.

HIV medication readiness and HIV medication-taking self-efficacy

Scores on the HIV medication-taking outcome expectancy scale increased with a significant change at the FU-2 point among all participants. When participants not presently on ART were analyzed separately, improvement in medication-taking outcome expectancy scale scores were also significantly higher at FU-2 than at baseline. Improvements were found only at FU-1 in scale scores of HIV medication-taking self-efficacy and medication-taking readiness among participants not presently on ART.

Social Capital

Participants tended to report greater network diversity at FU-1, an indicator suggesting greater range in supportive social capital resources.

Discussion

This study pilot tested an intervention to improve HIV care engagement by helping PLH mobilize social capital resources to support their care-related goals. Although population-level relationships between social capital and HIV health indicators have long been known, very few interventions have sought to use social capital models to improve HIV care outcomes. The intervention guided participants in identifying supportive resources and mobilizing supports for achieving HIV care goals. Unlike other social network or community-level interventions, this approach sought to harness the much broader range of social resources surrounding individuals—from family members to friends to HIV care providers—as potential social support resources. The pilot study provides preliminary evidence of the feasibility and acceptability of this approach.

Participants exhibited improvements over time on a number of HIV care indicators. Two measures of medication-taking adherence—the SPNS and the VAS—showed evidence of improvement at both followup points. In addition, medication-taking outcome expectancies improved over time and remained significantly greater at final followup relative to baseline. The proportion of participants with undetectable viral load increased by 13% at first followup and by nearly 20% at the second followup.

Over time, participants talked more often and with a greater number of supportive persons about living with HIV and HIV care topics. They also tended to expand in diversity of social capital resources following the intervention. These changes likely reflect increased social interactions because they occurred during the intervention period. The findings suggest that Lin’s theoretical approach of social capital mobilization has the potential to improve HIV care outcomes, a model that may be particularly useful given Russia’s highly-centralized HIV care system, limited community infrastructure and lack of HIV-focused nongovernmental organizations and care providers, dearth of community-based organizations, underfunded ART provision and limited coverage, stigma, and intolerant policies against HIV-vulnerable community populations. These structural factors may limit the effectiveness of any individual-based intervention.

Other limitations of this research must be noted. This test-of-concept intervention study is based a modest-sized sample and had limited statistical power. Participant recruitment through PLH community advertisements may have not reached all PLH community segments. This precludes an opportunity to estimate the number of persons exposed to these advertisements. In addition, this enrollment method may not have attracted persons who did not perceive the need or the potential benefit of the intervention. Persons who particularly lack social resources may require greater effort and time to develop their resources or strengthen their social relationships to fully benefit from this intervention. The absence of a control group precludes the determination of whether observed changes were due to the intervention or external factors. In addition, limited community coverage of the program may have reduced some intervention effects at the second followup. Intervention with ongoing boosters and reinforcement may be needed. Self-reports are susceptible to social desirability, recall inaccuracy, or interview-based data collection. To reduce potential bias, participants were assured that their data would never be associated with their name and be would identified only by a generic code. In addition, study staff who led the intervention sessions did not conduct followup interviews.

A full-scale and fully-powered evaluation is needed to establish the efficacy of this HIV care promotion intervention. Global HIV eradication goals are now being widely formulated and accepted, and interventions such as this can help to achieve these goals. Universal HIV care success can be achieved when PLH are supported in enrolling, adhering, and remaining in care, and when social capital is harnessed as a natural and affirmative source of support for HIV care.

Acknowledgments

This work was supported by the U.S. National Institute of Mental Health under Grants R01-MH098729, R01-MH113555, and P30-MH52776 and Russian Foundation for Basic Research under Grant 17-56-30026. The authors have no conflicts of interest to declare. The authors extend their appreciation to Anastasia Amirkhanian, Anastasia Meylakhs, Dmitry Mescheryakov, Larisa Glyzhina, Maria Donskaya, and Rudolph Amirkhanian, and the study participants.

Footnotes

Declaration of Interest Statement

Nothing to declare.

References

  1. Alemu H, Haile Mariam D, Tsui A, Ahmed S, & Shewamare A (2012). Effect of depressive symptoms and social support on weight and CD4 count increase at HIV clinic in Ethiopia. AIDS Care, 24, 866–876. [DOI] [PubMed] [Google Scholar]
  2. Amberbir A, Woldemichael K, Getachew S, Girma B, & Deribe K (2008). Predictors of adherence to antiretroviral therapy among HIV-infected persons: a prospective study in Southwest Ethiopia. BMC Public Health, 8, 265. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Balfour L, Tasca GA, Kowal J, Corace K, Cooper CL, Angel JB, … Cameron DW (2007). Development and validation of the HIV Medication Readiness Scale. Assessment, 14, 408–416. [DOI] [PubMed] [Google Scholar]
  4. Bourdieu P (1987). What makes social class?: On the theoretical and practical existence of groups. Berkeley Journal of Sociology, 32, 1–8. [Google Scholar]
  5. Campbell C, Scott K, Nhamo M, Nyamukapa C, Madanhire C, Skovdal M, … Gregson S (2013). Social capital and HIV competent communities: The role of community groups in managing HIV/AIDS in rural Zimbabwe. AIDS Care, 25(Suppl. 1), 114–122. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Campbell C, Skovdal M, Mupambireyi Z, Madanhire C, Nyamukapa C & Gregson S (2012). Building adherence-competent communities: Factors promoting children’s adherence to HIV/AIDS treatment in rural Zimbabwe. Health and Place, 18, 123–131. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Campbell C, Williams B, & Gilgen D (2002). In social capital a useful conceptual tool for exploring community level influences on HIV infection? An exploratory care study from South Africa. AIDS Care, 14, 41–54. [DOI] [PubMed] [Google Scholar]
  8. Cattell V (2001). Poor people, poor places, and poor health: The mediating role of social networks and social capital. Social Science and Medicine, 52, 1501–1516. [DOI] [PubMed] [Google Scholar]
  9. Catz SL, Kelly JA, Bogart LM, Benotsch EG, & McAuliffe TL (2000). Patterns, correlates, and barriers to medication adherence among persons prescribed new treatments for HIV disease. Health Psychology, 19, 124–133. [PubMed] [Google Scholar]
  10. Chang LW, Kagaayi J, Nakigozi G, Ssempijja V, Packer AH, Serwadda D, … Reynolds SJ (2010). Effect of peer health workers on AIDS care in Rakai, Uganda: a cluster-randomized trial. PLoS One, 5, e10923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Cohen MS, Doyle WU, Skoner DP, Rabin BS, & Gwaltney JM (1997). Social ties and susceptibility to the common cold. Journal of the American Medical Association, 277, 1940–1944. [PubMed] [Google Scholar]
  12. Coleman J (1990). The foundations of social theory. Cambridge, MA: Harvard University Press. [Google Scholar]
  13. Coleman J (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, S95–S120. [Google Scholar]
  14. Cousins S (2017). Number of new HIV infections is rising in Russia. BMJ, 358, j3543. [DOI] [PubMed] [Google Scholar]
  15. Desrosiers A, Blokhina E, Krupitsky E, Zvartau E, Schottenfeld R, & Chawarsky M (2017). Psychiatric symptoms, quality of life, and HIV status among people using opioids in Saint Petersburg, Russia. Drug and Alcohol Dependence, 172, 60–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Edelman EJ, Lunze K, Cheng DM, Lioznov DA, Quinn E, Gnatenko N, … Samet JH (2017). HIV stigma and substance use among HIV-positive Russians with risky drinking. AIDS and Behavior, 21, 2618–2627. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Erlen JA, Cha ES, Kim KH, Caruthers D, & Sereika SM (2010). The HIV Medication Taking Self-Efficacy Scale: psychometric evaluation. Journal of Advanced Nursing, 66, 2560–2572. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Frumence G, Killewo J, Kwesigabo G, Nystrom L, Eriksson M, & Emmelin M (2010). Social capital and the decline in HIV transmission: A case study in three villages in the Kagera region of Tanzania. SAHARA Journal, 7, 9–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Fuchs ER, Shapiro RY, & Minnite LC (2001). Social capital, political participation, and the urban community In Seagert SJ, Thompson P, & Warren MR (Eds.), Social capital and poor communities (pp. 290–324). New York: Russell Sage Foundation. [Google Scholar]
  20. Gibbs A, Campbell C, Akintola O, & Colvin C (2014). Social contexts and building social capital for collective action: Three case studies of volunteers in the context of HIV and AIDS in South Africa. Journal of Community and Applied Social Psychology, 25, 110–122. [Google Scholar]
  21. Goodness TM, Palfai TP, Cheng DM, Coleman SM, Bridden C, Blokhina E, … Samet JH (2014). Depressive symptoms and antiretroviral therapy (ART) initiation among HIV-infected Russian drinkers. AIDS and Behavior, 18, 1085–1093. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Harris J, Pillinger M, Fromstein D, Gomez B, Garris I, Kanetsky PA, … Gross R (2011). Risk factors for medication non-adherence in an HIV infected population in the Dominican Republic. AIDS Behavior, 15, 1410–1415. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Holtgrave DR, & Crosby RA (2003). Social capital, poverty, and income inequality as predictors of gonorrhea, syphilis, chlamydia, and AIDS case rates in the United States. Sexually Transmitted Infections, 79, 62–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. James SA, Schulz AJ, & van Olphen J (2001). Social capital, poverty, and community health: An explanation of linkages In Seagert SJ, Thompson P, & Warren MR (Eds.), Social capital and poor communities (pp. 165–186). New York: Russell Sage Foundation. [Google Scholar]
  25. Johnson MD, Dilworth SE, Taylor JM, Darbes LA, Comfort ML, & Neilands TB (2012). Primary relationships, HIV treatment adherence, and virologic control. AIDS and Behavior, 16, 1511–1521. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Julian FS, Martin P, & Erickson SR (2010). Validation of the Special Projects of National Significance adherence tool in HIV/AIDS patients. Annals of Pharmacotherapy, 44, 1003–1009. [DOI] [PubMed] [Google Scholar]
  27. Kalichman SC, Amaral CM, Swetzes C, Jones M, Macy R, Kalichman MO, & Cherry C (2009). A simple single-item rating scale to measure medication adherence: Further evidence for convergent validity. Journal of International Association of Providers of AIDS Care, 8, 367–374. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Kawachi I, Subramanian SV, & Kim D (2008). Social capital and health. New York: Springer. [Google Scholar]
  29. Kiriazova T, Lunze K, Raj A, Bushara N, Blokhina E, Krupitsky E., … Gifford AL (2017). “It is easier for me to shoot up”: Stigma, abandonment, and why HIV-positive drug users in Russia fail to link to HIV care. AIDS Care, 29, 559–563. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Khamarko K, & Myers JJ (2013). The influence of social support on the lives of HIV-infected individuals in low- and middle-income countries. Geneva: World Health Organization. [Google Scholar]
  31. Khumsaen N, Aoup-Por W, & Thammachak P (2012). Factors influencing quality of life among people living with HIV (PLWH) in Suphanburi Province, Thailand. Journal of the Association of Nurses in AIDS Care, 23, 63–72. [DOI] [PubMed] [Google Scholar]
  32. Knowlton AR, Arnsten JH, Gourevitch MN, Eldred L, Wilkinson JD, Rose CD, … INSPIRE Study Team. (2007). Microsocial environmental influences on highly active antiretroviral therapy outcomes among active injection drug users: The role of informal caregiving and household factors. Journal of Acquired Immune Deficiency Syndromes, 46(Suppl. 2), S110–S119. [DOI] [PubMed] [Google Scholar]
  33. Kuznetsova AV, Meylakhs AY, Amirkhanian YA, Kelly JA, Yakovlev AA, Musatov VB, & Amirkhanian AG (2016). Barriers and facilitators of HIV care engagement: Results of a qualitative study in St. Petersburg, Russia. AIDS and Behavior, 20, 2433–2443. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Lazarus RS, & Folkman S (1984). Stress, appraisal, and coping. New York: Springer. [Google Scholar]
  35. Lin N (1999a). Building a network theory of social capital. Connections, 22, 28–51. [Google Scholar]
  36. Lin N, (1999b). Social networks and status attainment. Annual Review of Sociology, 25, 467–487. [Google Scholar]
  37. Lin N, Fu YC, & Hsung RM (2001). The position generator: Measurement techniques for investigations of social capital In Lin N, Cook K, & Burt S (Eds.), Social capital. Theory and research (pp. 57–81). New Brunswick, NJ: Transaction. [Google Scholar]
  38. Malta M, Strathdee SA, Magnanini MF, & Bastos FI (2008). Adherence to antiretroviral therapy for human immunodeficiency virus/acquired immune deficiency syndrome among drug users: A systematic review. Addiction, 103, 1242–1257. [DOI] [PubMed] [Google Scholar]
  39. Pecoraro A, Mimiaga M, O’Cleirigh C, Safren J, Blokhina E, Verbitskaya E, … Woody GE (2015). Depression, substance use, viral load, and CD4+ count among patients who continued or left antiretroviral therapy for HIV in St. Petersburg, Russian Federation. AIDS Care, 27, 86–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Peltzer K, Friend-du Preez N, Ramlagan S, & Anderson J (2010). Antiretroviral treatment adherence among HIV patients in KwaZulu-Natal, South Africa. BMC Public Health, 10, 111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Poundstone KE, Strathdee SA, & Celentano DD (2004). The social epidemiology of human immunodeficiency virus/acquired immune deficiency syndrome. Epidemiologic Reviews, 26, 22–35. [DOI] [PubMed] [Google Scholar]
  42. Putnam RD (1993). Making democracy work: Civic traditions in modern Italy. Princeton, NJ: Princeton University Press. [Google Scholar]
  43. Ransome Y, Batson A, Galea S, Kawachi I, Nash D, & Mayer KH (2017a). The relationship between higher social trust and lower late HIV diagnosis and mortality differs by race/ethnicity: Results from a state-level analysis. Journal of the International AIDS Society, 20, 21442. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Ransome Y, Galea S, Pabayo R, Kawachi I, Braunstein S, & Nash D (2016). Social capital is associated with late HIV diagnosis: An ecological analysis. Journal of Acquired Immune Deficiency Syndromes, 73, 213–221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Ransome Y, Kawachi I, & Dean LT (2017b). Neighborhood social capital in relation to late HIV diagnosis, linkage to HIV care, and HIV care engagement. AIDS and Behavior, 21, 891–904. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Remien RH, Hirky AE, Johnson MD, Weinhardt LS, Whittier D, & Le GM (2003). Adherence to medication treatment: A qualitative study of facilitators and barriers among a diverse sample of HIV+ men and women in four US cities. AIDS and Behavior, 7, 61–72. [DOI] [PubMed] [Google Scholar]
  47. Rotheram-Borus MJ, Stein JA, Jiraphongsa C, Khumtong S, Lee SJ, & Li L (2010). Benefits of family and social relationships for Thai parents living with HIV. Prevention Science, 11, 298–307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Russian Federal AIDS Center. (2015). HIV Infection: Informational Bulletin #40. [In Russian]. Moscow, Russia: 2015. Retrieved from: http://www.hivrussia.ru/files/bul_40.pdf [Google Scholar]
  49. Russian Federal AIDS Center. (2017). HIV infection in Russian Federation in 2017. Moscow: Russian Federal AIDS Center; Retrieved from: http://aids-centr.perm.ru/images/4/hiv_in_russia/hiv_in_rf_31.12.2017.pdf [Google Scholar]
  50. Simoni JM, Frick PA, & Huang B (2006). A longitudinal evaluation of a social support model of medication adherence among HIV-positive men and women on antiretroviral therapy. Health Psychology, 25, 74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Tiyou A, Belachew T, Alemseged F, & Biadgilign S (2010). Predictors of adherence to antiretroviral therapy among people living with HIV/AIDS in resource-limited setting of southwest Ethiopia. AIDS Research and Therapy, 7, 39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. UNAIDS. (1998). HIV Infections in Eastern Europe. Geneva: UNAIDS. [Google Scholar]
  53. UNAIDS. (2018). UNAIDS Data 2018. Geneva: UNAIDS. [Google Scholar]
  54. Villalonga-Olives E, Wind, TR, & Ksawachi, I (2018). Social capital interventions in public health: A systematic review. Social Science and Medicine, 212, 203–218. [DOI] [PubMed] [Google Scholar]
  55. Wills TA, & Fegan MF (2001). Social networks and social support In Baum A, Revenson TA, & Singer JE (Eds.), Handbook of health psychology (pp. 209–234). Mahwah NH: Erlbaum. [Google Scholar]
  56. Ware NC, Idoko J, Kaaya S, Biraro IA, Wyatt M, Agbaji O, … Bangsberg DR (2009). Explaining adherence success in Sub-Saharan Africa: An ethnographic study. PLoS Medicine, 6, e10000011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Wohl AR, Galvan FH, Myers HF, Garland W, George S, Witt M, … Lee ML (2011). Do social support, stress, disclosure, and stigma influence retention in HIV care for Latino and African American men who have sex with men? AIDS and Behavior, 15, 1098–1110. [DOI] [PubMed] [Google Scholar]

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